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» Regularization Networks and Support Vector Machines
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ICDM
2005
IEEE
161views Data Mining» more  ICDM 2005»
15 years 3 months ago
Making Logistic Regression a Core Data Mining Tool with TR-IRLS
Binary classification is a core data mining task. For large datasets or real-time applications, desirable classifiers are accurate, fast, and need no parameter tuning. We presen...
Paul Komarek, Andrew W. Moore
SMC
2010
IEEE
132views Control Systems» more  SMC 2010»
14 years 8 months ago
Selection of SIFT feature points for scene description in robot vision
This paper presents a method for selection of SIFT(Scale-Invariant Feature Transform) feature points using OC-SVM (One Class-Support Vector Machines). We proposed the method for au...
Yuya Utsumi, Masahiro Tsukada, Hirokazu Madokoro, ...
BMCBI
2008
137views more  BMCBI 2008»
14 years 9 months ago
A dynamic Bayesian network approach to protein secondary structure prediction
Background: Protein secondary structure prediction method based on probabilistic models such as hidden Markov model (HMM) appeals to many because it provides meaningful informatio...
Xin-Qiu Yao, Huaiqiu Zhu, Zhen-Su She
BMCBI
2007
207views more  BMCBI 2007»
14 years 9 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...
BIBM
2008
IEEE
172views Bioinformatics» more  BIBM 2008»
15 years 4 months ago
Boosting Methods for Protein Fold Recognition: An Empirical Comparison
Protein fold recognition is the prediction of protein’s tertiary structure (Fold) given the protein’s sequence without relying on sequence similarity. Using machine learning t...
Yazhene Krishnaraj, Chandan K. Reddy